Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method of receiving and managing networked communications configuring a vehicle insurance policy, the method comprising: receiving vehicle behavior data, the vehicle behavior data measuring a driving behavior; generating, by a premium calculating engine in response to receiving the vehicle behavior data, a modified premium using the vehicle behavior data; determining that a difference between an initial premium and the modified premium exceeds a threshold value, wherein the initial premium is for an insurance policy covering a vehicle associated with the vehicle behavior data; and modifying the vehicle insurance policy to immediately implement the modified premium.
This invention relates to dynamic vehicle insurance policy management based on real-time driving behavior data. The system addresses the problem of static insurance premiums that do not reflect current driving habits, leading to either overcharging safe drivers or undercharging risky drivers. The method involves collecting vehicle behavior data, such as speed, braking patterns, and acceleration, which quantifies driving behavior. A premium calculating engine processes this data to generate a modified insurance premium that more accurately reflects the driver's risk profile. If the difference between the initial premium and the modified premium exceeds a predefined threshold, the system automatically adjusts the insurance policy to implement the new premium immediately. This ensures that premiums are dynamically updated based on actual driving performance, promoting fairness and risk-based pricing. The system may also include additional features like data validation, policy compliance checks, and user notifications to ensure transparency and accuracy in premium adjustments. By continuously monitoring and adjusting premiums, the invention aims to create a more responsive and equitable insurance model for vehicle owners.
2. The method of claim 1 , wherein the vehicle behavior data is further calculated by systems operated by an underwriter of the vehicle insurance policy using vehicle performance data.
3. The method of claim 2 , wherein the vehicle performance data includes at least one of vehicle speed, g-load, mileage, acceleration, deceleration, engine performance, oil temperature, fluid levels, cylinder temperature, spark plug voltage, fuel-air mixture, fuel flow, air pressure, boost pressure, or emissions gas readings.
4. The method of claim 1 , wherein the vehicle behavior data is aggregated from one or more drivers operating the vehicle without regard to any individual driver.
5. The method of claim 1 , further comprising: receiving external data from a source other than the vehicle.
6. The method of claim 5 , wherein the external data includes aggregate behavior data from one or more members of a demographic.
7. The method of claim 1 , wherein the vehicle behavior data is calculated at the vehicle.
A system and method for processing vehicle behavior data involves collecting and analyzing data related to vehicle operations to improve safety, efficiency, or performance. The invention addresses the challenge of accurately assessing vehicle behavior in real-time or near-real-time to enable timely decision-making, such as collision avoidance, route optimization, or predictive maintenance. The method includes gathering vehicle behavior data from various sensors, such as speed, acceleration, braking patterns, steering angles, and environmental conditions. This data is processed locally at the vehicle, eliminating the need for external processing or cloud-based analysis. By performing calculations onboard, the system reduces latency, enhances privacy, and ensures reliability even in areas with limited connectivity. The vehicle behavior data may include dynamic metrics like lateral acceleration, yaw rate, or wheel slip, which are derived from raw sensor inputs. Advanced algorithms analyze these metrics to detect anomalies, predict potential failures, or optimize driving strategies. The processed data can be used for immediate actions, such as adjusting vehicle controls, or stored for long-term trend analysis. This approach improves vehicle safety by enabling rapid responses to hazardous conditions and reduces dependency on external infrastructure. It also supports autonomous driving systems by providing real-time insights into vehicle dynamics. The invention is applicable to various vehicle types, including passenger cars, commercial trucks, and industrial machinery.
8. The method of claim 1 , wherein the vehicle behavior data is generated by a data processing module.
This method outlines a process for dynamically adjusting vehicle insurance policies. It begins by receiving vehicle behavior data, which measures driving patterns and is specifically generated by a **data processing module**. A premium calculating engine then uses this received vehicle behavior data to generate a modified insurance premium. The system determines if the difference between the vehicle's current (initial) insurance premium and the newly calculated modified premium exceeds a predefined threshold. If this condition is met, the vehicle insurance policy is immediately updated to implement the modified premium. ERROR (embedding): Error: Failed to save embedding: Could not find the 'embedding' column of 'patent_claims' in the schema cache
9. A system, comprising: a data processing module installed in a vehicle including a hardware sensor for measuring vehicle performance data; and a computer-readable code for receiving and managing network communications, the computer-readable code being stored on a computer-readable medium, and, when executed, causing a computer processor to: receive vehicle behavior data, the vehicle behavior data measuring a driving behavior; generate, by a premium calculating engine in response to receiving the vehicle behavior data, a modified premium using the vehicle behavior data; determine that a difference between an initial premium and the modified premium exceeds a threshold value, wherein the initial premium is for an insurance policy covering a vehicle associated with the vehicle behavior data; and modify the vehicle insurance policy to immediately implement the modified premium.
10. The computer-readable code of claim 9 , wherein the vehicle behavior data is further calculated by systems operated by an underwriter of the vehicle insurance policy using the vehicle performance data.
11. The computer-readable code of claim 9 , wherein the vehicle data is aggregated from one or more drivers operating the vehicle without regard to any individual driver.
The invention relates to a system for processing vehicle data collected from multiple drivers without associating the data with any specific individual. The system includes computer-readable code that aggregates and analyzes vehicle data, such as driving behavior, performance metrics, or operational conditions, from one or more drivers operating the same vehicle. The aggregation process ensures that the data is collected and processed in a way that does not identify or track individual drivers, maintaining anonymity. This approach allows for broader analysis of driving patterns, vehicle performance, and other relevant metrics without privacy concerns. The system may also include additional features, such as generating reports or insights based on the aggregated data, which can be used for fleet management, safety improvements, or vehicle maintenance. The invention addresses the need for privacy-preserving data collection in vehicle monitoring systems, enabling organizations to gather valuable insights while protecting driver anonymity. The aggregated data can be used to identify trends, optimize vehicle usage, or enhance safety protocols without compromising individual privacy.
12. The computer-readable code of claim 9 , wherein the computer-readable code, when executed, causes the computer processor to receive external data from a source other than the vehicle.
13. The computer-readable code of claim 12 , wherein the external data includes aggregate behavior data from one or more members of a demographic.
14. The computer-readable code of claim 9 , wherein the vehicle performance data includes at least one of vehicle speed, g-load, mileage, acceleration, deceleration, engine performance, oil temperature, fluid levels, cylinder temperature, spark plug voltage, fuel-air mixture, fuel flow, air pressure, boost pressure, or emissions gas′readings.
15. The computer-readable code of claim 9 , wherein the vehicle behavior data is generated by a data processing module.
The invention relates to systems for processing vehicle behavior data to improve vehicle operations. The problem addressed is the need for efficient and accurate analysis of vehicle behavior data to enhance safety, performance, and decision-making in autonomous or semi-autonomous vehicles. The invention involves a data processing module that generates vehicle behavior data by analyzing sensor inputs, such as vehicle speed, acceleration, braking patterns, steering angles, and environmental conditions. This data is then used to detect anomalies, predict potential hazards, or optimize vehicle control strategies. The data processing module may employ machine learning algorithms, statistical models, or rule-based systems to interpret the raw sensor data and derive meaningful insights. The generated vehicle behavior data can be transmitted to a central server for further analysis or used locally by the vehicle's onboard systems to adjust driving parameters in real time. The invention aims to provide a robust and scalable solution for monitoring and improving vehicle behavior, reducing the risk of accidents and enhancing overall driving efficiency.
16. A system, comprising: a data processing module installed in a vehicle including a hardware sensor for measuring vehicle performance data; and a device for receiving and managing electronic communications, the device comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to: receive vehicle behavior data, the vehicle behavior data measuring a driving behavior; generate, by a premium calculating engine in response to receiving the vehicle behavior data, a modified premium using the vehicle behavior data; determine that a difference between an initial premium and the modified premium exceeds a threshold value, wherein the initial premium is for an insurance policy covering a vehicle associated with the vehicle behavior data; and modify the vehicle insurance policy to immediately implement the modified premium.
17. The device of claim 16 , wherein the vehicle behavior data is further calculated by systems operated by an underwriter of the vehicle insurance policy using the vehicle performance data.
The invention relates to a system for analyzing vehicle behavior data to assess risk for insurance purposes. The system collects vehicle performance data, such as speed, acceleration, braking patterns, and cornering behavior, from sensors or onboard diagnostics. This data is processed to generate vehicle behavior data, which reflects driving habits and risk factors. The system includes a data processing module that calculates risk metrics based on the behavior data, which are then used by an underwriter to determine insurance policy terms, premiums, or coverage adjustments. The underwriter's systems further refine the behavior data by applying proprietary algorithms or risk models to enhance accuracy. The system may also integrate external data sources, such as traffic conditions or road infrastructure, to provide a comprehensive risk assessment. The goal is to enable dynamic, data-driven insurance pricing and risk management tailored to individual driving behaviors.
18. The device of claim 16 , wherein the vehicle data is aggregated from one or more drivers operating the vehicle without regard to any individual driver.
19. The device of claim 16 , wherein the processor is configured to receive external data from a source other than the vehicle.
20. The device of claim 19 , wherein the external data includes aggregate behavior data from one or more members of a demographic.
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February 23, 2021
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